雷达对抗侦察数据关联规律挖掘算法研究

Related rules mining algorithm of radar countermeasures reconnaissance data

目前,雷达对抗侦察数据的分析和总结主要依靠情报分析员的经验和知识,随着侦察数据与日剧增以及战时极大量数据的可能出现,人工分析侦察数据变得捉襟见肘。数据挖掘的渐渐兴起和挖掘算法的不断改进,使得这个问题的解决有了可能。根据雷达对抗侦察数据的特点和作战运用要求,运用数据挖掘方法,分析了雷达对抗侦察数据关联规律挖掘算法,并给出了基于权重的挖掘算法、强关联规律挖掘算法以及备用信号挖掘算法。

Now, the analysis and summing of the data that reconnoitered by radar countermeasure equip- ment mainly depend on the experience and knowledge of intelligence analyzers. With the increasing of the re-connaissance data and the possibility of the emergence of large number of data in wartime, the analysis of re-connaissance data becomes hard to handle. The popularity of data mining and the development of mining algo-rithms give the chance to solve the problem. According to the characteristic of radar countermeasure reconnais- sance data and the needs of operation, using data mining methods, the algorithms of radar countermeasure re-connaissance data related rules mining algorithm are analyzed, and the mining algorithm depends upon factor quality, the mining algorithm of strong related rules and the mining algorithm of backup signal are given.